Low-centered Polygons Research Articles

Degradation of ice-wedge polygons leads to increased fluxes of water and DOC

Ice-wedge polygon landscapes make up a substantial part of high-latitude permafrost landscapes. The hydrological conditions shape how these landscapes store and release organic carbon. However, their coupled water‑carbon dynamics are poorly understood as field measurements are sparse in smaller catchments and coupled hydrology-dissolved organic carbon (DOC) models are not tailored for these landscapes. Here we present a model that simulates the hydrology and associated DOC export of high-centered and low-centered ice-wedge polygons and apply the model to a small catchment with abundant polygon coverage along the Yukon Coast, Canada. The modeled seasonal pattern of water and carbon fluxes aligns with sparse field data. These modeled seasonal patterns indicate that early-season runoff is mostly surficial and generated by low-centered polygons and snow trapped in troughs of high-centered polygons. High-centered polygons show potential for deeper subsurface flow under future climate conditions. This suggests that high-centered polygons will be responsible for an increasing proportion of annual DOC export compared to low-centered polygons. Warming likely shifts low-centered polygons to high-centered polygons, and our model shows that this shift will cause a deepening of the active layer and a lengthening of the thawing season. This, in turn, intensifies seasonal runoff and DOC flux, mainly through its duration. Our model provides a physical hypothesis that can be used to further quantify and refine our understanding of hydrology and DOC export of arctic ice-wedge polygon terrain.

Modelling growing season carbon fluxes at a low-center polygon ecosystem in the Mackenzie River Delta

A temporal upscaling study was conducted to estimate net ecosystem exchange (NEE) of carbon dioxide and net methane exchange (NME) for a low-center polygon (LCP) ecosystem in the Mackenzie River Delta, for each of the 11 growing seasons (2009–2019). We used regression models to create a time series of flux drivers from in situ weather observations (2009–2019) combined with ERA5 reanalysis and satellite data. We then used neural networks that were trained and validated on a single growing season (2017) of eddy covariance data to model NEE and NME over each growing season. The study indicates growing season NEE was negative (net uptake) and NME was positive (net emission) in this LCP ecosystem. Cumulative carbon (C) uptake was estimated to be −46.7 g C m−2 (CI95% ± 45.3) per growing season, with methane emissions offsetting an average 5.6% of carbon dioxide uptake (in g C m−2) per growing season. High air temperatures (>15 °C) reduced daily CO2 uptake and cumulative NEE was positively correlated with mean air growing season temperatures. Cumulative NME was positively correlated with the length of the growing season. Our analysis suggests warmer climate conditions may reduce carbon uptake in this LCP ecosystem.

Monitoring Ground Surface Deformation of Ice-Wedge Polygon Areas in Saskylakh, NW Yakutia, Using Interferometric Synthetic Aperture Radar (InSAR) and Google Earth Engine (GEE)

As one of the best indicators of the periglacial environment, ice-wedge polygons (IWPs) are important for arctic landscapes, hydrology, engineering, and ecosystems. Thus, a better understanding of the spatiotemporal dynamics and evolution of IWPs is key to evaluating the hydrothermal state and carbon budgets of the arctic permafrost environment. In this paper, the dynamics of ground surface deformation (GSD) in IWP zones (2018–2019) and their influencing factors over the last 20 years in Saskylakh, northwestern Yakutia, Russia were investigated using the Interferometric Synthetic Aperture Radar (InSAR) and Google Earth Engine (GEE). The results show an annual ground surface deformation rate (AGSDR) in Saskylakh at −49.73 to 45.97 mm/a during the period from 1 June 2018 to 3 May 2019. All the selected GSD regions indicate that the relationship between GSD and land surface temperature (LST) is positive (upheaving) for regions with larger AGSDR, and negative (subsidence) for regions with lower AGSDR. The most drastic deformation was observed at the Aeroport regions with GSDs rates of −37.06 mm/a at tower and 35.45 mm/a at runway. The GSDs are negatively correlated with the LST of most low-centered polygons (LCPs) and high-centered polygons (HCPs). Specifically, the higher the vegetation cover, the higher the LST and the thicker the active layer. An evident permafrost degradation has been observed in Saskylakh as reflected in higher ground temperatures, lusher vegetation, greater active layer thickness, and fluctuant numbers and areal extents of thermokarst lakes and ponds.

New insights into the drainage of inundated ice-wedge polygons using fundamental hydrologic principles

Abstract. The pathways and timing of drainage from the inundated centers of ice-wedge polygons in a warming climate have important implications for carbon flushing, advective heat transport, and transitions from methane to carbon dioxide dominated emissions. Here, we expand on previous research using a recently developed analytical model of drainage from a low-centered polygon. Specifically, we perform (1) a calibration to field data identifying necessary model refinements and (2) a rigorous model sensitivity analysis that expands on previously published indications of polygon drainage characteristics. This research provides intuition on inundated polygon drainage by presenting the first in-depth analysis of drainage within a polygon based on hydrogeological first principles. We verify a recently developed analytical solution of polygon drainage through a calibration to a season of field measurements. Due to the parsimony of the model, providing the potential that it could fail, we identify the minimum necessary refinements that allow the model to match water levels measured in a low-centered polygon. We find that (1) the measured precipitation must be increased by a factor of around 2.2, and (2) the vertical soil hydraulic conductivity must decrease with increasing thaw depth. Model refinement (1) accounts for runoff from rims into the ice-wedge polygon pond during precipitation events and possible rain gauge undercatch, while refinement (2) accounts for the decreasing permeability of deeper soil layers. The calibration to field measurements supports the validity of the model, indicating that it is able to represent ice-wedge polygon drainage dynamics. We then use the analytical solution in non-dimensional form to provide a baseline for the effects of polygon aspect ratios (radius to thaw depth) and coefficient of hydraulic conductivity anisotropy (horizontal to vertical hydraulic conductivity) on drainage pathways and temporal depletion of ponded water from inundated ice-wedge polygon centers. By varying the polygon aspect ratio, we evaluate the relative effect of polygon size (width), inter-annual increases in active-layer thickness, and seasonal increases in thaw depth on drainage. The results of our sensitivity analysis rigorously confirm a previous analysis indicating that most drainage through the active layer occurs along an annular region of the polygon center near the rims. This has important implications for transport of nutrients (such as dissolved organic carbon) and advection of heat towards ice-wedge tops. We also provide a comprehensive investigation of the effect of polygon aspect ratio and anisotropy on drainage timing and patterns, expanding on previously published research. Our results indicate that polygons with large aspect ratios and high anisotropy will have the most distributed drainage, while polygons with large aspect ratios and low anisotropy will have their drainage most focused near their periphery and will drain most slowly. Polygons with small aspect ratios and high anisotropy will drain most quickly. These results, based on parametric investigation of idealized scenarios, provide a baseline for further research considering the geometric and hydraulic complexities of ice-wedge polygons.

Untargeted Exometabolomics Provides a Powerful Approach to Investigate Biogeochemical Hotspots with Vegetation and Polygon Type in Arctic Tundra Soils

Rising temperatures in the Arctic have led to the thawing of tundra soils, which is rapidly changing terrain, hydrology, and plant and microbial communities, causing hotspots of biogeochemical activity across the landscape. Despite this, little is known about how nutrient-rich low molecular weight dissolved organic matter (LMW DOM) varies within and across tundra ecosystems. Using a high-resolution nano-liquid chromatography-mass spectrometry (LC/MS) approach, we characterized the composition and availability of LMW DOM from high-centered polygons (HCP) and low-centered polygons (LCP) with Eriophorum angustifolium or Carex aquatilis as the dominant vegetation. Over 3000 unique features (i.e., discrete mass/charge ions) were detected; 521 were identified as differentially abundant between polygonal types and 217 were putatively annotated using high mass accuracy MS data. While polygon type was a strong predictor of LMW DOM composition and availability, vegetation and soil depth were also important drivers. Extensive evidence was found for enhanced microbial processing at the LCP sites, which were dominated by Carex plant species. We detected significant differences between polygon types with varying aboveground landscape features or properties, and hotspots of biogeochemical activity, indicating LMW DOM, as quantified by untargeted exometabolomics, provides a window into the dynamic complex interactions between landscape topography, vegetation, and organic matter cycling in Arctic polygonal tundra soils.

Temporal, Spatial, and Temperature Controls on Organic Carbon Mineralization and Methanogenesis in Arctic High-Centered Polygon Soils.

Warming temperatures in continuous permafrost zones of the Arctic will alter both hydrological and geochemical soil conditions, which are strongly linked with heterotrophic microbial carbon (C) cycling. Heterogeneous permafrost landscapes are often dominated by polygonal features formed by expanding ice wedges: water accumulates in low centered polygons (LCPs), and water drains outward to surrounding troughs in high centered polygons (HCPs). These geospatial differences in hydrology cause gradients in biogeochemistry, soil C storage potential, and thermal properties. Presently, data quantifying carbon dioxide (CO2) and methane (CH4) release from HCP soils are needed to support modeling and evaluation of warming-induced CO2 and CH4 fluxes from tundra soils. This study quantifies the distribution of microbial CO2 and CH4 release in HCPs over a range of temperatures and draws comparisons to previous LCP studies. Arctic tundra soils were initially characterized for geochemical and hydraulic properties. Laboratory incubations at −2, +4, and +8°C were used to quantify temporal trends in CO2 and CH4 production from homogenized active layer organic and mineral soils in HCP centers and troughs, and methanogen abundance was estimated from mcrA gene measurements. Results showed that soil water availability, organic C, and redox conditions influence temporal dynamics and magnitude of gas production from HCP active layer soils during warming. At early incubation times (2–9 days), higher CO2 emissions were observed from HCP trough soils than from HCP center soils, but increased CO2 production occurred in center soils at later times (>20 days). HCP center soils did not support methanogenesis, but CH4-producing trough soils did indicate methanogen presence. Consistent with previous LCP studies, HCP organic soils showed increased CO2 and CH4 production with elevated water content, but HCP trough mineral soils produced more CH4 than LCP mineral soils. HCP mineral soils also released substantial CO2 but did not show a strong trend in CO2 and CH4 release with water content. Knowledge of temporal and spatial variability in microbial C mineralization rates of Arctic soils in response to warming are key to constraining uncertainties in predictive climate models.

Arctic insect emergence timing and composition differs across thaw ponds of varying morphology

ABSTRACT Freshwater ponds provide habitats for aquatic insects that emerge and subsidize consumers in terrestrial ecosystems. In the Arctic, insects provide an important seasonal source of energy to birds that breed and rear young on the tundra. The abundance and timing of insect emergence from arctic thaw ponds is poorly understood, but understanding these fluxes is important, given the role of insects in food webs and current rates of environmental change at high latitudes. We aimed to evaluate emerging insect communities from thaw ponds with different morphologies, identify environmental covariates influencing insect composition, and describe temporal changes in insect abundance. We collected environmental information and insects that emerged over two growing seasons and examined the phenology and taxonomic composition of insects arising from different pond classes: low centered polygon, small coalescent, large coalescent, and trough ponds. Our findings indicated no differences in the timing of total emergence across ponds of varying morphology. Community dissimilarity was primarily associated with center or margin habitat and variables that differed strongly among pond classes. These insects, which provide important provisions for various species of birds, are likely to experience changes in emergence phenology and composition due to ongoing, rapid warming in the region.

A Model of Ice Wedge Polygon Drainage in Changing Arctic Terrain

As ice wedge degradation and the inundation of polygonal troughs become increasingly common processes across the Arctic, lateral export of water from polygonal soils may represent an important mechanism for the mobilization of dissolved organic carbon and other solutes. However, drainage from ice wedge polygons is poorly understood. We constructed a model which uses cross-sectional flow nets to define flow paths of meltwater through the active layer of an inundated low-centered polygon towards the trough. The model includes the effects of evaporation and simulates the depletion of ponded water in the polygon center during the thaw season. In most simulations, we discovered a strong hydrodynamic edge effect: only a small fraction of the polygon volume near the rim area is flushed by the drainage at relatively high velocities, suggesting that nearly all advective transport of solutes, heat, and soil particles is confined to this zone. Estimates of characteristic drainage times from the polygon center are consistent with published field observations.

N-Alkane Characteristics of Thawed Permafrost Deposits Below a Thermokarst Lake on Bykovsky Peninsula, Northeastern Siberia

Rapid permafrost thaw by thermokarst mobilizes previously frozen organic matter (OM) down to tens of meters deep within decades to centuries, leading to microbial degradation and greenhouse gas release. Late Pleistocene ice-rich Yedoma deposits that thaw underneath thermokarst lakes and refreeze after lake drainage are called taberal sediments. Although widespread, these have not been the subject of many studies. To study OM characteristics and degradability in thawed Yedoma, we obtained a 31.5 m long core from beneath a thermokarst lake on the Bykovsky Peninsula, northeastern Siberia. We reported radiocarbon ages, biogeochemical parameters (organic carbon (OC) content and bulk carbon isotopes) and n-alkane distributions. We found the most degraded OM in frozen, fluvial sediments at the bottom of the core, as indicated by the lowest n-alkane odd-over-even predominance (OEP; 2.2). Above this, the thawed Yedoma sediments had an n-alkane distribution typical of emergent vegetation, suggesting a landscape dominated by low-centered polygons. These sediments were OC poor (OC content: 0.8 wt%, 60% of samples <0.1 wt%), but the OM (OEP~5.0) was better preserved than in the fluvial sediments. The upper part of the Yedoma reflected a transition to a drier, grass dominated environment. Furthermore, this unit’s OM was least degraded (OEP~9.4). The thermokarst lake that formed about 8 cal ka BP thawed the Yedoma in the talik and deposited Holocene lake sediments containing well-preserved OM (OEP~8.4) with the highest n-alkane concentrations (20.8 μg g-1 sediment). Old, allochthonous OM was found in the thawed Yedoma and frozen fluvial deposits. Using an n-alkane endmember model, we identified a mixed OM input in all units. In our study, the thawed Yedoma sediments contained less OC than reported in other studies for still frozen Yedoma. The Yedoma OM was more degraded compared to previous biomarker research on frozen Yedoma. However, this signal is overprinted by the input signal. The fluvial deposits below the Yedoma contained more OM, but this OM was more degraded, which can be explained by the OM input signal. Continued talik deepening and expansion of this thermokarst lake and others similar to it will expose OM with heterogeneous properties to microbial degradation.

Understanding the relative importance of vertical and horizontal flow in ice-wedge polygons

Abstract. Ice-wedge polygons are common Arctic landforms. The future of these landforms in a warming climate depends on the bidirectional feedback between the rate of ice-wedge degradation and changes in hydrological characteristics. This work aims to better understand the relative roles of vertical and horizontal water fluxes in the subsurface of polygonal landscapes, providing new insights and data to test and calibrate hydrological models. Field-scale investigations were conducted at an intensively instrumented location on the Barrow Environmental Observatory (BEO) near Utqiaġvik, AK, USA. Using a conservative tracer, we examined controls of microtopography and the frost table on subsurface flow and transport within a low-centered and a high-centered polygon. Bromide tracer was applied at both polygons in July 2015 and transport was monitored through two thaw seasons. Sampler arrays placed in polygon centers, rims, and troughs were used to monitor tracer concentrations. In both polygons, the tracer first infiltrated vertically until encountering the frost table and was then transported horizontally. Horizontal flow occurred in more locations and at higher velocities in the low-centered polygon than in the high-centered polygon. Preferential flow, influenced by frost table topography, was significant between polygon centers and troughs. Estimates of horizontal hydraulic conductivity were within the range of previous estimates of vertical conductivity, highlighting the importance of horizontal flow in these systems. This work forms a basis for understanding complexity of flow in polygonal landscapes.

Mechanistic Modeling of Microtopographic Impacts on CO2 and CH4 Fluxes in an Alaskan Tundra Ecosystem Using the CLM‐Microbe Model

AbstractSpatial heterogeneities in soil hydrology have been confirmed as a key control on CO2 and CH4 fluxes in the Arctic tundra ecosystem. In this study, we applied a mechanistic ecosystem model, CLM‐Microbe, to examine the microtopographic impacts on CO2 and CH4 fluxes across seven landscape types in Utqiaġvik, Alaska: trough, low‐centered polygon (LCP) center, LCP transition, LCP rim, high‐centered polygon (HCP) center, HCP transition, and HCP rim. We first validated the CLM‐Microbe model against static‐chamber measured CO2 and CH4 fluxes in 2013 for three landscape types: trough, LCP center, and LCP rim. Model application showed that low‐elevation and thus wetter landscape types (i.e., trough, transitions, and LCP center) had larger CH4 emissions rates with greater seasonal variations than high‐elevation and drier landscape types (rims and HCP center). Sensitivity analysis indicated that substrate availability for methanogenesis (acetate, CO2 + H2) is the most important factor determining CH4 emission, and vegetation physiological properties largely affect the net ecosystem carbon exchange and ecosystem respiration in Arctic tundra ecosystems. Modeled CH4 emissions for different microtopographic features were upscaled to the eddy covariance (EC) domain with an area‐weighted approach before validation against EC‐measured CH4 fluxes. The model underestimated the EC‐measured CH4 flux by 20% and 25% at daily and hourly time steps, suggesting the importance of the time step in reporting CH4 flux. The strong microtopographic impacts on CO2 and CH4 fluxes call for a model‐data integration framework for better understanding and predicting carbon flux in the highly heterogeneous Arctic landscape.

Deep Convolutional Neural Networks for Automated Characterization of Arctic Ice-Wedge Polygons in Very High Spatial Resolution Aerial Imagery

The microtopography associated with ice-wedge polygons governs many aspects of Arctic ecosystem, permafrost, and hydrologic dynamics from local to regional scales owing to the linkages between microtopography and the flow and storage of water, vegetation succession, and permafrost dynamics. Wide-spread ice-wedge degradation is transforming low-centered polygons into high-centered polygons at an alarming rate. Accurate data on spatial distribution of ice-wedge polygons at a pan-Arctic scale are not yet available, despite the availability of sub-meter-scale remote sensing imagery. This is because the necessary spatial detail quickly produces data volumes that hamper both manual and semi-automated mapping approaches across large geographical extents. Accordingly, transforming big imagery into ‘science-ready’ insightful analytics demands novel image-to-assessment pipelines that are fueled by advanced machine learning techniques and high-performance computational resources. In this exploratory study, we tasked a deep-learning driven object instance segmentation method (i.e., the Mask R-CNN) with delineating and classifying ice-wedge polygons in very high spatial resolution aerial orthoimagery. We conducted a systematic experiment to gauge the performances and interoperability of the Mask R-CNN across spatial resolutions (0.15 m to 1 m) and image scene contents (a total of 134 km2) near Nuiqsut, Northern Alaska. The trained Mask R-CNN reported mean average precisions of 0.70 and 0.60 at thresholds of 0.50 and 0.75, respectively. Manual validations showed that approximately 95% of individual ice-wedge polygons were correctly delineated and classified, with an overall classification accuracy of 79%. Our findings show that the Mask R-CNN is a robust method to automatically identify ice-wedge polygons from fine-resolution optical imagery. Overall, this automated imagery-enabled intense mapping approach can provide a foundational framework that may propel future pan-Arctic studies of permafrost thaw, tundra landscape evolution, and the role of high latitudes in the global climate system.

Spatial and temporal variations of thaw layer thickness and its controlling factors identified using time-lapse electrical resistivity tomography and hydro-thermal modeling

Quantitative understanding of controls on thaw layer thickness (TLT) dynamics in the Arctic peninsula is essential for predictive understanding of permafrost degradation feedbacks to global warming and hydrobiochemical processes. This study jointly interprets electrical resistivity tomography (ERT) measurements and hydro-thermal numerical simulation results to assess spatiotemporal variations of TLT and to determine its controlling factors in Barrow, Alaska. Time-lapse ERT measurements along a 35-m transect were autonomously collected from 2013 to 2015 and inverted to obtain soil electrical resistivity. Based on several probe-based TLT measurements and co-located soil electrical resistivity, we estimated the electrical resistivity thresholds associated with the boundary between the thaw layer and permafrost using a grid search optimization algorithm. Then, we used the obtained thresholds to derive the TLT from all soil electrical resistivity images. The spatiotemporal analysis of the ERT-derived TLT shows that the TLT at high-centered polygons (HCPs) is smaller than that at low-centered polygons (LCPs), and that both thawing and freezing occur earlier at the HCPs compared to the LCPs. In order to provide a physical explanation for dynamics in the thaw layer, we performed 1-D hydro-thermal simulations using the community land model (CLM). Simulation results showed that air temperature and precipitation jointly govern the temporal variations of TLT, while the topsoil organic content (SOC) and polygon morphology are responsible for its spatial variations. When the topsoil SOC and its thickness increase, TLT decreases. Meanwhile, at LCPs, a thicker snow layer and saturated soil contribute to a thicker TLT and extend the time needed for TLT to freeze and thaw. This research highlights the importance of combination of measurements and numerical modeling to improve our understanding spatiotemporal variations and key controls of TLT in cold regions.

Evaporation dominates evapotranspiration on Alaska’s Arctic Coastal Plain

ABSTRACT The dynamics of evapotranspiration (ET), such as the partitioning to evaporation and transpiration, of polygonal ground on the Arctic Coastal Plain are not well understood. We assessed ET dynamics, including evaporation and transpiration partitioning, created by microtopographic features associated with high- and low-centered polygons. Chamber ET and leaf-level transpiration measurements were conducted in one-week field campaigns in two growing seasons with contrasting weather conditions. We found that ET was greater in the drier and warmer sampling period (2013) compared to the colder and wetter one (2014). Evaporation dominated ET, particularly in the wetter and colder sampling period (>90% in 2014 vs. 80% in 2013). In the 2013 sampling period, wetter and warmer conditions increased ET and the contribution of transpiration to ET. If the soils warm with degrading permafrost, ET and the fraction contributed by transpiration may increase to a certain threshold, when moisture must increase with rising temperatures to further increase these fluxes. While the fraction of transpiration may rise with warmer soils, it is unlikely that transpiration will completely dominate ET. This work highlights the complexities of understanding ET in this dynamic environment and the importance of understanding differences across polygonal ground.

Late Holocene ice-wedge polygon dynamics in northeastern Siberian coastal lowlands

ABSTRACT Ice-wedge polygons are common features of northeastern Siberian lowland periglacial tundra landscapes. To deduce the formation and alternation of ice-wedge polygons in the Kolyma Delta and in the Indigirka Lowland, we studied shallow cores, up to 1.3 m deep, from polygon center and rim locations. The formation of well-developed low-center polygons with elevated rims and wet centers is shown by the beginning of peat accumulation, increased organic matter contents, and changes in vegetation cover from Poaceae-, Alnus-, and Betula-dominated pollen spectra to dominating Cyperaceae and Botryoccocus presence, and Carex and Drepanocladus revolvens macro-fossils. Tecamoebae data support such a change from wetland to open-water conditions in polygon centers by changes from dominating eurybiontic and sphagnobiontic to hydrobiontic species assemblages. The peat accumulation indicates low-center polygon formation and started between 2380 ± 30 and 1676 ± 32 years before present (BP) in the Kolyma Delta. We recorded an opposite change from open-water to wetland conditions because of rim degradation and consecutive high-center polygon formation in the Indigirka Lowland between 2144 ± 33 and 1632 ± 32 years BP. The late Holocene records of polygon landscape development reveal changes in local hydrology and soil moisture.

Spatial variability of CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; uptake in polygonal tundra: assessing low-frequency disturbances in eddy covariance flux estimates

Abstract. The large spatial variability in Arctic tundra complicates the representative assessment of CO2 budgets. Accurate measurements of these heterogeneous landscapes are, however, essential to understanding their vulnerability to climate change. We surveyed a polygonal tundra lowland on Svalbard with an unmanned aerial vehicle (UAV) that mapped ice-wedge morphology to complement eddy covariance (EC) flux measurements of CO2. The analysis of spectral distributions showed that conventional EC methods do not accurately capture the turbulent CO2 exchange with a spatially heterogeneous surface that typically features small flux magnitudes. Nonlocal (low-frequency) flux contributions were especially pronounced during snowmelt and introduced a large bias of −46 gC m−2 to the annual CO2 budget in conventional methods (the minus sign indicates a higher uptake by the ecosystem). Our improved flux calculations with the ogive optimization method indicated that the site was a strong sink for CO2 in 2015 (−82 gC m−2). Due to differences in light-use efficiency, wetter areas with low-centered polygons sequestered 47 % more CO2 than drier areas with flat-centered polygons. While Svalbard has experienced a strong increase in mean annual air temperature of more than 2 K in the last few decades, historical aerial photographs from the site indicated stable ice-wedge morphology over the last 7 decades. Apparently, warming has thus far not been sufficient to initiate strong ice-wedge degradation, possibly due to the absence of extreme heat episodes in the maritime climate on Svalbard. However, in Arctic regions where ice-wedge degradation has already initiated the associated drying of landscapes, our results suggest a weakening of the CO2 sink in polygonal tundra.

Mapping snow depth within a tundra ecosystem using multiscale observations and Bayesian methods

Abstract. This paper compares and integrates different strategies to characterize the variability of end-of-winter snow depth and its relationship to topography in ice-wedge polygon tundra of Arctic Alaska. Snow depth was measured using in situ snow depth probes and estimated using ground-penetrating radar (GPR) surveys and the photogrammetric detection and ranging (phodar) technique with an unmanned aerial system (UAS). We found that GPR data provided high-precision estimates of snow depth (RMSE = 2.9 cm), with a spatial sampling of 10 cm along transects. Phodar-based approaches provided snow depth estimates in a less laborious manner compared to GPR and probing, while yielding a high precision (RMSE = 6.0 cm) and a fine spatial sampling (4 cm × 4 cm). We then investigated the spatial variability of snow depth and its correlation to micro- and macrotopography using the snow-free lidar digital elevation map (DEM) and the wavelet approach. We found that the end-of-winter snow depth was highly variable over short (several meter) distances, and the variability was correlated with microtopography. Microtopographic lows (i.e., troughs and centers of low-centered polygons) were filled in with snow, which resulted in a smooth and even snow surface following macrotopography. We developed and implemented a Bayesian approach to integrate the snow-free lidar DEM and multiscale measurements (probe and GPR) as well as the topographic correlation for estimating snow depth over the landscape. Our approach led to high-precision estimates of snow depth (RMSE = 6.0 cm), at 0.5 m resolution and over the lidar domain (750 m × 700 m).

Sedimentary ancient DNA and pollen reveal the composition of plant organic matter in Late Quaternary permafrost sediments of the Buor Khaya Peninsula (north-eastern Siberia)

Abstract. Organic matter deposited in ancient, ice-rich permafrost sediments is vulnerable to climate change and may contribute to the future release of greenhouse gases; it is thus important to get a better characterization of the plant organic matter within such sediments. From a Late Quaternary permafrost sediment core from the Buor Khaya Peninsula, we analysed plant-derived sedimentary ancient DNA (sedaDNA) to identify the taxonomic composition of plant organic matter, and undertook palynological analysis to assess the environmental conditions during deposition. Using sedaDNA, we identified 154 taxa and from pollen and non-pollen palynomorphs we identified 83 taxa. In the deposits dated between 54 and 51 kyr BP, sedaDNA records a diverse low-centred polygon plant community including recurring aquatic pond vegetation while from the pollen record we infer terrestrial open-land vegetation with relatively dry environmental conditions at a regional scale. A fluctuating dominance of either terrestrial or swamp and aquatic taxa in both proxies allowed the local hydrological development of the polygon to be traced. In deposits dated between 11.4 and 9.7 kyr BP (13.4–11.1 cal kyr BP), sedaDNA shows a taxonomic turnover to moist shrub tundra and a lower taxonomic richness compared to the older samples. Pollen also records a shrub tundra community, mostly seen as changes in relative proportions of the most dominant taxa, while a decrease in taxonomic richness was less pronounced compared to sedaDNA. Our results show the advantages of using sedaDNA in combination with palynological analyses when macrofossils are rarely preserved. The high resolution of the sedaDNA record provides a detailed picture of the taxonomic composition of plant-derived organic matter throughout the core, and palynological analyses prove valuable by allowing for inferences of regional environmental conditions.

Movements and Habitat Use of White-Fronted Geese (Anser albifrons frontalis) During the Remigial Molt in Arctic Alaska, USA

Abstract. Proposed oil and gas leasing in the National Petroleum Reserve - Alaska has raised questions about possible impacts of development on molting Greater White-fronted Geese (Anser albifrons frontalis) and their habitats. We used GPS transmitters to record fine-scale location data of molting and post-molt White-fronted Geese to assess patterns of movement and resource selection relative to vegetation class, year (2012, 2013), and body mass at capture. Molting White-fronted Geese were located an average of 63.3 ± 4.9 m (SE) from lakeshores. Estimated terrestrial home range size for flightless birds differed between years (2012 = 13.2 ± 2.6 km2; 2013 = 6.5 ± 1.8 km2), but did not vary among habitat strata or with body mass. Molting White-fronted Geese used sedge (Carex aquatilus) dominated low centered polygons and water more frequently than expected given proportional habitat availability, but avoided tussock tundra and wet sedge vegetation classes. Upon regaining flight, individuals tended to remain...

Numerical Modelling of Ice-Wedge Polygon Geomorphic Transition

A numerical model is presented to test whether a hillslope diffusion approach can simulate the topographic evolution of some recently developed high-centred ice-wedge polygons south of Prudhoe Bay, Alaska. The polygons are adjacent to a highway whose construction appears to have triggered their geomorphic transition. The model is calibrated using a light detection and ranging data-set that captures both the high-centred polygons and some neighbouring low-centred polygons that appear to be unaffected by thermokarst. The latter are used to represent initial conditions. Model simulations are analysed to estimate potential fluxes of soil from polygon edges into troughs and the loss of depressional water storage during development of the high-centred polygons. Overall, a match between the topography of simulated and observed high-centred polygons suggests that diffusive hillslope processes represent a feasible mechanism driving polygon transition. Rates of soil displacement inferred from optimised simulations, moreover, are within the range previously observed in permafrost terrain with a similar climate. Direct observations of the soil velocity profile in actively transitioning polygons would help resolve whether and to what extent hillslope processes, as opposed to pure thaw-related subsidence at the polygon edges, drive the development of high-centred forms in natural systems. Copyright © 2016 John Wiley & Sons, Ltd.